Abstract
Blur estimation is critical to blind image deconvolution. In this work, by taking Gaussian kernel as an example, we propose an approach to estimate the blur size for photon-limited images. This estimation is based on the minimization of a novel criterion, blur-PURE (Poisson unbiased risk estimate), which makes use of the Poisson noise statistics of the measurement. Experimental results demonstrate the effectiveness of the proposed method in various scenarios. This approach can be then plugged into our recent PURE-LET deconvolution algorithm, and an example on real fluorescence microscopy is presented.
| Original language | English |
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| Title of host publication | 2017 IEEE International Conference on Image Processing |
| Subtitle of host publication | Proceedings |
| Publisher | IEEE |
| Pages | 495-499 |
| Number of pages | 5 |
| ISBN (Electronic) | 9781509021758, 978-1-5090-2174-1 |
| ISBN (Print) | 978-1-5090-2176-5 |
| DOIs | |
| Publication status | Published - Sept 2017 |
| Externally published | Yes |
| Event | 24th IEEE International Conference on Image Processing (ICIP 2017) - China National Convention Center, Beijing, China Duration: 17 Sept 2017 → 20 Sept 2017 http://2017.ieeeicip.org/ |
Publication series
| Name | Proceedings - International Conference on Image Processing, ICIP |
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| ISSN (Print) | 1522-4880 |
| ISSN (Electronic) | 2381-8549 |
Conference
| Conference | 24th IEEE International Conference on Image Processing (ICIP 2017) |
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| Abbreviated title | ICIP |
| Place | China |
| City | Beijing |
| Period | 17/09/17 → 20/09/17 |
| Internet address |
Funding
This work was supported by grants from the Research Grants Council of Hong Kong (AoE/M-05/12, CUHK14200114), and in part by the National Natural Science Foundation of China (61401013).
Research Keywords
- Image deconvolution
- Parametric blur estimation
- Photon-limited images
- Poisson noise